Impact of deep learning-based image reconstruction on image quality and lesion visibility in renal computed tomography at different doses.

ABSTRACT:

Background

Numerous computed tomography (CT) image reconstruction algorithms have been developed to improve image quality, and high-quality renal CT images are crucial to clinical diagnosis. This study evaluated the image quality and lesion visibility of deep learning-based image reconstruction (DLIR) compared with adaptive statistical iterative reconstruction-Veo (ASiR-V) in contrast-enhanced renal CT at different reconstruction strengths and doses.

Methods

From January 2020 to May 2021, we prospectively included 101 patients who underwent renal contrast-enhanced CT scanning (69 at 120 kV; 32 at 80 kV). All image data were reconstructed with ASiR-V (30% and 70%) and DLIR at low, medium, and high reconstruction strengths (DLIR-L, DLIR-M, and DLIR-H, respectively). The CT num

SUBMITTER: Bie Y 

PROVIDER: S-EPMC10102763 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature